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1.
Health Aff (Millwood) ; 43(2): 287-296, 2024 02.
Artigo em Inglês | MEDLINE | ID: mdl-38315934

RESUMO

Landlords are essential actors within the rental housing market, and there is much to be learned about their willingness to participate in rental assistance programs that improve access to stable housing. Because the success of these programs, such as the Mobility (Location-Based) Voucher program in Pittsburgh, Pennsylvania, can be derailed by landlord opposition, it is important to test strategies that increase landlords' participation. Using data from a unique survey of Pittsburgh landlords, we found that exposing landlords to an asset-framing narrative that highlighted the social, economic, and health benefits of receiving a mobility voucher increased landlords' reported willingness to rent to a mobility voucher recipient by 21 percentage points. Reported willingness was also higher among landlords who believed that housing affordability was connected to health. Our findings offer insight into how to increase landlords' participation in affordable housing programs that require their engagement to succeed.


Assuntos
Habitação , Humanos , Custos e Análise de Custo , Pennsylvania
2.
BMC Health Serv Res ; 19(1): 614, 2019 Aug 30.
Artigo em Inglês | MEDLINE | ID: mdl-31470849

RESUMO

BACKGROUND: This study aims to assess geographical distribution of hospitals and extent of inequalities in hospital beds against socioeconomic status (SES) of residents of five metropolitan cities in Iran. METHODS: A cross-sectional analysis was conducted to measure geographical inequality in hospital and hospital bed distributions of 68 districts in five metropolitan cities during 2016 using geographic information system (GIS), and Gini and Concentration indices. Correlation analysis was performed to show the relationship between the SES and inequality in hospital beds densities. RESULTS: The study uncovered marked inequalities in hospitals and hospital beds distributions. The Gini indices for hospital beds were greater than 0.55. The aggregated concentration indices for public and private hospital beds were 0.33 and 0.49, respectively. The GIS revealed that 216 (70.6%) hospitals were located in two highest socioeconomic status classes in the cities. Only 29 (9.5%) hospitals were located in the lowest class. The public, private, and the cumulative hospitals beds distributions in Tehran and Esfahan showed significant (p < 0.05) positive correlation with SES of the residents. CONCLUSIONS: The high inequalities in hospital and hospital beds distributions in our study imply an overlooked but growing concern for geographical access to healthcare in rapidly urbanizing metropolitan cities in Iran. Thus, regardless of ownership, decision-makers should emphasize the disadvantaged areas in metropolitan cities when need arises for the establishment of new healthcare facilities in order to ensure fairness in healthcare. The metropolitan cities and rapid urbanization settings in other countries could learn lessons to reduce or prevent similar issues which might have hampered access to healthcare.


Assuntos
Ocupação de Leitos/estatística & dados numéricos , Acessibilidade aos Serviços de Saúde/estatística & dados numéricos , Disparidades em Assistência à Saúde/estatística & dados numéricos , Hospitais Urbanos/provisão & distribuição , Cidades , Estudos Transversais , Geografia , Humanos , Irã (Geográfico) , Densidade Demográfica , Classe Social , Fatores Socioeconômicos
3.
Health Policy Plan ; 32(5): 669-675, 2017 Jun 01.
Artigo em Inglês | MEDLINE | ID: mdl-28453720

RESUMO

OBJECTIVE: Access to hospitals in megacities in low and middle income countries might be hampered by travel barriers and distance. We assessed the 'inverse care law' hypothesis: whether hospitals tended to be built in the relatively better-off areas through the time. METHODS: A longitudinal time-series study (1966 to 2011) in Tehran to measure inequality in the distribution of hospital beds. We assessed correlations between the district socioeconomic status and availability of hospital beds via regression analyses, estimated correlation, Gini and concentration indices, and used GIS models to map hospital distributions through time. FINDING: We found a clear relationship between socioeconomic status and number of hospital beds per capita ( P -values <0.05). Gini coefficients were about 0.6 and 0.8 for public and private beds, respectively. A third of the variations in hospital bed distribution was explained by the welfare status of the district. For every extra residential room per capita, 130 to 280 extra beds were observed per ten thousand population at the district level. In 2011, out of 162 hospitals, 110 were located in six districts around the centre and northern part of the city. During the time period only two private hospitals were built in relatively disadvantaged districts. CONCLUSION: Over a period of about fifty years new hospitals had been established in the relatively affluent areas of the city and the relationship between socioeconomic status of district with total, private and public beds were direct and intensive. Results indicate the problem of inequality may remain over time and be resistant to policy initiatives and major political changes.


Assuntos
Acessibilidade aos Serviços de Saúde , Número de Leitos em Hospital/estatística & dados numéricos , Hospitais Urbanos/estatística & dados numéricos , Fatores Socioeconômicos , Geografia , Irã (Geográfico)
4.
Iran J Public Health ; 44(6): 848-54, 2015 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-26258098

RESUMO

BACKGROUND: One of the major health policy issues, in the both developed and developing countries, is the equality in the distribution of health resources. The aim of this study was to investigate the disparity in the distribution of health physical resources across the provinces of Iran in 2001 and 2011. METHODS: This was a cross-sectional retrospective study which investigated inequality in the distribution of health physical resources by three indexes of Gini Coefficient, Gaswirth index and Index of Dissimilarity. The data on provinces were obtained from the yearbook statistics and Ministry of Health, and Medical Education. The Excel software was used to calculated indexes. RESULTS: The finding showed the mean Gini Coefficient for all variables was 0.178 in 2001 and 0.158 in 2011. Besides, the mean Gaswirth index and index of dissimilarity were 11.5 and 1.5% in 2001 and 11 and 1.4% in 2011, respectively. CONCLUSION: There was slightly inequality in distribution of physical health resources in Iran. According to the results of three indexes, this study showed when Tehran province excluding from total sample, the inequality was decreased.

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